Applied Scientist II: Driving Partner Growth with ML

Amazon; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

RSUs

Job summary

Amazon is seeking an Applied Scientist to design, build, and productionize ML/AI and econometric solutions that improve how advertisers work with partners in the Seattle area. You will solve high-impact problems with autonomy and collaborate with product, data engineering, and sales teams.

The role requires strong modeling, A/B testing, and experience with AWS data and ML platforms, plus a track record mentoring peers and delivering business outcomes in a fast-moving environment.

Qualifications

• 3+ years building models for business applications.
• PhD or Master's degree with 4+ years in CS/CE/ML.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms, data structures, numerical optimization, data mining, parallel and distributed computing.
• 3+ years of hands-on predictive modeling and large data analysis.

Responsibilities

• Design, prototype, validate, and productionize ML models end-to-end.
• Own production science models and deploy with monitoring and refinement.
• Design and run A/B experiments to validate impact on partner growth and ad spend.
• Collaborate with MLOps and Data Engineering to power science with curated datasets.
• Translate model outputs into business impact and communicate with cross-functional teams.
• Contribute to model quality monitoring and data quality frameworks.
• Mentor teammates and foster knowledge sharing.

Skills

Java

C++

Python

Algorithms & data structures

Predictive modeling

A/B testing

Cloud computing

Education

MS/PhD in CS/CE/ML

Tools

AWS (SageMaker)

Andes data infra

SQL/BigQuery

Job description

Amazon is seeking an Applied Scientist to design, build, and productionize ML/AI and econometric solutions that improve how advertisers work with partners in the Seattle area. You will solve high-impact problems with autonomy and collaborate with product, data engineering, and sales teams.

The role requires strong modeling, A/B testing, and experience with AWS data and ML platforms, plus a track record mentoring peers and delivering business outcomes in a fast-moving environment.